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Sparse Recovery Optimization in Wireless Sensor Networks with a Sub-Nyquist Sampling Rate

  • Published:2015-07-10 Issue:7 Volume:15 Page:16654-16673
  • ISSN:1424-8220
  • Container-title:Sensors
  • language:en
  • Short-container-title:Sensors

Author:

Brunelli Davide,Caione Carlo

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 28 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

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2. A Novel Deep Learning Framework for Efficient Automatic Modulation Recognition of Sub-Nyquist Sampled Signals;2023 22nd International Symposium on Communications and Information Technologies (ISCIT);2023-10-16

3. Resource Optimization of Stream Processing in Layered Internet of Things;2023 42nd International Symposium on Reliable Distributed Systems (SRDS);2023-09-25

4. Compressive Sensing Strategy on Sparse Array to Accelerate Ultrasonic TFM Imaging;IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control;2023-06

5. An Improved Data Compression Framework for Wireless Sensor Networks Using Stacked Convolutional Autoencoder (S-CAE);SN Computer Science;2023-05-24
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